| 研究生: |
陳俊彰 Chen, Chun-Chang |
|---|---|
| 論文名稱: |
以擴散模型分析半導體晶圓代工公司營收增長趨勢 Using diffusion theory to analyze the revenue trend of a semiconductor company |
| 指導教授: |
呂執中
Lyu, Jr-Jung |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 高階管理碩士在職專班(EMBA) Executive Master of Business Administration (EMBA) |
| 論文出版年: | 2022 |
| 畢業學年度: | 110 |
| 語文別: | 中文 |
| 論文頁數: | 61 |
| 中文關鍵詞: | Bass 擴散模型 、半導體 、晶圓代工 、多世代模型 |
| 外文關鍵詞: | Bass diffusion model, semiconductor, wafer foundry, multi-generation model |
| 相關次數: | 點閱:62 下載:12 |
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半導體產業是台灣規模最大的科技產業,尤其是晶圓代工(2021年)的市佔率全球超過65%。更由於近年來半導體大量的研發跟投資,造成大部分半導體廠退出高階製程的研發,晶圓代工向為我國重點發展的科技產業。值此摩爾定律快達到物理極限的挑戰下,一線業者莫仍然努力突破技術開發先進技術半,導體技術此被在此背景下也快速不斷的推出新世代的製程和產品。
而針對新世代產品的擴散過程,許多學者結合產品生命周期做市場需求的預測與分析。但在大量世代的技術下讓資料的處理與分析變的異常困難,大量的參數的造成準確度不佳大多學者都局限在三代以下的產品做分析。
本研究利用Bass 模型進行各代產品的分析,並利用各半導體單代產品的模型分析的配適度進行分類與合併,並提出一個以非線性迴歸R2為依據的方法進行世代之間的合併,依此將多個世代擴散簡化為三個世代以進行分析,如此可進行較長較多市代的模型分析,又不會因為太多世代的資料影響分析的複雜度和準確度。最後本研究以半導體晶圓代工龍頭公司為案例進行實證分析,分析結果對於舊世代的營收預測準確度MAPE約10%~25%,最新一代技術營收預測準確度MAPE約5%~10%,最佳可到4.4% 的準確度。
關鍵字: Bass 擴散模型,半導體,多世代模型,晶圓代工
The semiconductor industry is Taiwan's largest technology industry, with a global market share of more than 60% for wafer foundry. Due to the large amount of R&D investment in recent years, most semiconductor factories have withdrawn from the research and development of high-end processes. As Moore's Law is about to reach the physical limit of the challenge, the first-line company is still striving to break through technology to develop advanced semiconductor technology and rapidly introducing a new generation of processes and products.
In view of the diffusion process of the new generation of products, this study uses the Bass diffusion model for the analysis of semiconductor products revenue of each generation. Through in-depth analysis, each semiconductor single generation of products is classified. A nonlinear regression R2-based method for inter-generational merger is adopted to simplify the diffusion of multiple generations into three generations for analysis.
Finally, an empirical analysis was conducted based on the data from a leading semiconductor wafer foundry company, and the analysis results show an accuracy of about 10% to 25% for the revenue forecast accuracy of the old generation. The accuracy of the latest generation technology revenue forecasting is about 5% to 10%, and the optimal accuracy could reach 4.4%.
Keywords: Bass diffusion model, semiconductor, multi-generation model, wafer foundry
中文文獻
謝欣儒,多世代產品進入市場時間之研究-以資訊軟體業為例,2011年,成功大學碩士論文
英文文獻
Bass, F. M., "A New Product Growth for Model Consumer Durables", Management Science, Vol. 15, 5, pp. 215-227, 1969.
Bass, F. M., Comment on "A New Product Growth for Model Consumer Durables," Management Science, Vol. 50, 12, pp. 1833-1840, 2004.
Chih-Hsuan Wang , Hsuan-Chen Lin, "Competitive substitution and technological diffusion for semiconductor foundry firms,"Advanced Engineering Informatics, 48 (2021) 101254
Chen-Fu Chien a,n , Yun-Ju Chen , Jin-Tang Peng, " Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle," Int. J. Production Economics, 128(2010) 496-509
Coccia M. 2019. "Theories of the evolution of technology based on processes of competitive substitution and multi-mode interaction between technologies," Journal of Economics Bibliography, vol. 6, n. 2, pp. 99-109C
Jiang, Z., & Sarkar, S.,"Speed Matters: The Role of Free Software Offer in Software Diffusion," Journal of Management Information Systems Vol. 26, 3, pp. 207-239, 2009.
Jerome Massiani, Andreas Gohs.,"The Choice of Bass model coefficients to forecast diffusion for innovative product: An emperical investigation for new automative technologies," Research in Transporation Economics, Vol. 50, pp.17-28, 2015
Koca, E.,Souza, G. C., & Druehl, C. T.,"Managing Product Rollovers," Decision Sciences, Vol. 41, 2, pp. 403-423, 2010.
Li, Y., & Jin, Y. H.,"Racing to Market Leadership: Product Launch and Upgrade Decisions," International Journal of Production Economics, Vol. 119, 2, pp. 284-297, 2009.
Langerak, F.,Griffin, A., & Hultink, E. J.,"Balancing Development Costs and Sales to Optimize the Development Time of Product Line Additions," Journal of Product Innovation Management, Vol. 27, 3, pp. 336-348, 2010.
Moriarty, R. T., & Kosnik, T. J.,"High-Tech Marketing: Concepts, Continuity, and Change," Sloan Management Review, Vol. 7, 4, pp. 7-17, 1989.
Mahajan, V.,Muller, E., & Srivastava, R. K.,"Determination of Adopter Categories by Using Innovation Diffusion-Models," Journal of Marketing Research, Vol. 27, 1, pp. 37-50, 1990.
Mahajan, V., & Muller, E.,"Timing, Diffusion, and Substitution of Successive Generations of Technological Innovations: The IBM Mainframe Case," Technological Forecasting and Social Change, Vol. 51, 2, pp. 109-132, 1996.
Mohr, J. Marketing of High-Technology Products and Innovations. Prentice-Hall: Upper Saddle River,NJ.2001.
Norton, J. A., & Bass, F. M.,"A Diffusion-Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, Vol. 33, 9, pp. 1069-1086, 1987.
Rogers, E. M., "Diffusion of innovation," New York: The Free Press, 1995
Ying-Jen Chen & Chen-Fu Chien, "An Impirical study of demand forecasting of non-volatele memory for smart poduction of simiconductor manufacturing," Internation Journal of Production Research, 56:13, 4629-4643, 2018